The invention relates to a method for the preparation of an obstacle map and of a correspondingly designed electronic control device.
Acquisition of the environment of the vehicle is indispensable for many future driving functions and driver assistance systems of a vehicle, in particular automatic driving, parking assistant, etc. In particular it is usually necessary to establish which segments of the environment are not blocked by obstacles and can thus be driven on without restriction. The acquisition of the environment is here carried out with various sensor systems such as camera groups, radar, lidar and ultrasonic sensors. An environment map, frequently also called an occupancy grid, is typically used as a model for modeling the environment of a vehicle for different driver assistance systems based on cameras or generally on sensors (e.g. a parking assistant).
An environment map comprises environment data that results from processing sensor measurements of the environment, and which represents them. The environment data is here usually arranged according to segments of the environment. The environment data that results from measurements in a segment is assigned to that segment. The environment data can comprise different types of information, depending on the cell, for example the occupancy probability of the respective cell (i.e. the probability that the cell is occupied by an obstacle), the height of the obstacle, and so forth.
To model the environment, many driver assistance functions do not require the abstract occupancy probability as information, but rather the information as to whether a segment of the environment is occupied by an obstacle or not. An obstacle in a segment signifies here that the segment of the environment cannot be driven on at all with the vehicle, or only under certain conditions.
To provide the obstacle information, an obstacle map is typically generated comprising cells, each of which is assigned to segments of the environment of the vehicle, and to each of which the information as to whether the corresponding segment of the environment is occupied by an obstacle is assigned. Typically the cells of the obstacle map correspond to the cells of the environment map and the associated segments are the same. The information as to whether a segment is occupied by an obstacle is determined through the comparison of the occupancy probability of the environment map assigned to the segment with a threshold value. In many versions it is moreover possible to take the obstacle height determined for the segment into account.
Sensor systems are known in the motor vehicle field that can detect obstacles by means of a method known as “Structure From Motion” (SFM) using sequential camera recordings of the vehicle taken from different positions. This detection is, however, often faulty. Therefore, in order to generate meaningful occupancy probabilities in an environment map, the occupancy probability of a segment detected by SFM is often computationally modified with previously detected occupancy probabilities of the same segment. An accumulation of the detected occupancy probabilities of a cell of the environment map thus takes place.
At the same time, in the SFM method, the correct detection of the occupancy probability by an obstacle in a segment depends on the distance from the vehicle and on the angle to the longitudinal vehicle axis. Obstacles directly in front of the vehicle, for example, are more frequently recognized incorrectly than obstacles to the side of the vehicle. Even with an accumulation of the occupancy probabilities determined in a temporal sequence, obstacles in the environment map are represented by different occupancy probabilities.
When the obstacle map is generated on the basis of the environment map through the formation of threshold values, the problem thus arises that obstacles that, as a result of the detection characteristics of SFM, are only inadequately represented by occupancy probabilities, are not recorded in the obstacle map.
An aspect of the invention relates to a method for the preparation of an obstacle map, wherein the obstacle map comprises cells, each of which is assigned to segments of the environment of the vehicle, and to each of which the information as to whether the corresponding segment of the environment is occupied by an obstacle is assigned, wherein the method comprises: the preparation of an environment map, wherein the environment map contains cells, each of which is assigned to segments of the environment of the vehicle, and to each of which an obstacle probability is assigned that represents the probability that the corresponding segment of the environment is occupied by an obstacle; the preparation of a threshold value specification; wherein the threshold value specification for cells of the environment map specifies different threshold values; wherein the threshold value specification is determined depending on the trajectory, in particular on a part of the previous trajectory, of the vehicle; determination of the obstacle map on the basis of the environment map and depending on the threshold value specification. The threshold value specification can comprise an explicit statement of threshold values for each cell of the environment map (also known as the threshold value map), or can be represented in a closed form (formula) from which the threshold value for individual cells of the environment map can be determined. The threshold value map is sometimes also called the exploration grid. Sensor readings from a plurality of sensor systems, such as measurements from camera systems and ultrasonic systems, can be included in the preparation of the environment map. At the same time, the threshold value specification can take the detection properties (in particular the dependency on direction and distance) of the sensor system of the vehicle into account, with which the occupancy probabilities of the environment segments are determined.
It is thus proposed at this point that a constant threshold value, as in the prior art, is not used, but rather a threshold value that varies depending on the segment (or depending on the cell). The variation of the threshold value can be selected in such a way that the different detection properties of obstacles by the sensors of the vehicle are taken into account. A higher threshold value is chosen for those segments for which the detection properties of the sensor represent obstacles with a high occupancy probability. Conversely, a lower threshold value is selected for those segments in which obstacles are represented by lower occupancy probabilities. The threshold values specified for the segments by the threshold value pattern can also depend on the driving function that is being carried out on the basis of the obstacle map.
The trajectory of the vehicle is a part of this consideration. It determines those segments for which the sensor properties are effective, i.e. in which segments of the environment obstacles are represented with a high occupancy probability, and in which segments obstacles are represented with a low occupancy probability. Typically the threshold value specification will set a lower threshold value for environment segments in the direction of travel in front of the vehicle than for segments that the former driving trajectory has passed to the side.
In this way obstacles located more remotely in front of the vehicle in the direction of travel are also correctly detected in the creation of the obstacle map. At the same time, obstacles that, due to the sensor properties, are to a larger extent detected (and have a correspondingly higher occupancy probability in the environment map) are also detected. Noise which frequently occurs in those regions in which, due to the sensor properties, obstacles are represented by high occupancy probabilities, is also effectively suppressed in the creation of the obstacle map.
In an advantageous implementation, a threshold value pattern is repeatedly taken into account for determination of the threshold value specification; wherein the threshold value pattern gives different threshold value increments for different cells of a group of cells. The number of cells in the group of cells can be smaller than the number of cells of the environment map. The threshold value pattern can be a threshold value pattern map which specifies threshold value increments for individual cells. The threshold values given by the pattern advantageously follow a Gaussian function or a linear function. The threshold value pattern here reflects the properties of the obstacle detection of the sensor system in the case of a single measurement (wherein a single measurement here is to be understood as the data basis with which the updating of the environment map is performed, and which can very well incorporate a plurality of raw measurements). The threshold value pattern can also take the properties of different sensor systems, for example SFM camera systems and ultrasound, into account. Complex threshold value patterns can result from this.
The threshold value pattern is typically applied or taken into account repeatedly without change. A specified initial threshold value specification can be the starting point. The threshold value pattern is repeatedly added to this, this being done depending on the trajectory of the motor vehicle. The threshold value of individual cells of the environment map can here be limited to a maximum value of, for example, 0.9.
The incremental development of the threshold value specification entails the advantage that each sequential determination of the obstacle map can be built on top of the previous threshold value specification. Only the threshold value pattern corresponding to the current vehicle position is added to the most recently determined threshold value specification. The new vehicle position can also be reflected by a shift in the environment map or of its contents.
As long as the updating of the environment map (on the basis of new sensor measurements) takes place at regular intervals of time or distance, the accumulation (or the preparation of the updated threshold value pattern) can be carried out in the same time segments or, if the incorporation depends on covering a drive path, according to predetermined distance sections of the drive trajectory.
One or a plurality of considerations or accumulations (additions) to the threshold value pattern can be performed between the determination of a pair of obstacle maps, in order to determine the threshold value specification that is then to be applied. This can depend on the number of new sensor measurements incorporated (i.e. on their newly detected occupancy probabilities of the segments of the environment). The threshold value pattern, in particular the height of the threshold value increments, can also depend on the number of updates to the environment map through respective, new sensor measurements of the environment.
The threshold value pattern can be taken into account in the determination of the threshold value specification depending on the position and/or alignment of the vehicle in the environment map. This thus means that when the threshold value pattern is applied to the initial threshold value map, the threshold value increments to be added in the individual cells of the threshold value map (based on the specifications of the threshold value pattern) are determined with reference to the vehicle position. In other words: the threshold value pattern comprises a reference point, for example the symmetrical point of the pattern (and potentially also a reference direction), which is oriented to the vehicle position (and potentially the vehicle orientation).
In advantageous implementations, the same segment of the environment is assigned to each cell of the environment map as cells of the obstacle map; wherein the information for a cell of the obstacle map is obtained through a comparison of the occupancy probability of the corresponding cell of the environment map with a threshold value given for the corresponding cell of the environment map in accordance with the threshold value specification. The cell structures of the obstacle map and the environment map thus correspond to one another.
Another aspect of the invention relates to an electronic control device for vehicles, wherein the control device is designed to execute one of the methods described above. The control device can be a microcontroller, a CPU, an ASIC or RISC. A further aspect of the invention relates to a vehicle, in particular an automobile, comprising the control device.
Other objects, advantages and novel features of the present invention will become apparent from the following detailed description of one or more preferred embodiments when considered in conjunction with the accompanying drawings.
The same reference signs refer to corresponding elements across the figures.